A Python implementation of the Gaussian Processes framework with Bayesian Optimization. Fit noiseless or noisy data and use existing or custom kernels. Bayesian optimization module using existing acquisition functions (μ+kσ, PI) or custom.
See Notebooks
- numpy
Gaussian Processes for Machine Learning book
Carl Edward Rasmussen and Christopher K. I. Williams
http://www.gaussianprocess.org/gpml/